A genetic algorithm approach to the machine-component grouping problem with multiple objectives

Sustainability Formation of Machine Cells in Group Technology Systems Using Modified Artificial Bee Colony Algorithm

“…A lower value of cell load variation is preferable, since it leads to efficient flow of parts and lowers the inventory level. The cumulative cell load variation is measured using the formula suggested [15].…”

“…In the present days, most of the cell formation problems have been solved by using meta-heuristic algorithms. Meta-heuristic search approaches, such as simulated annealing [12][13][14] and a genetic algorithm [15], have also been used to solve various cell formation problems. Prabhakaran [16] has discussed the cell load variation and intercellular moves in cell formation problem using genetic algorithm (GA).…”

Integrated Cellular Manufacturing System Design and Layout Using Group Genetic Algorithms

“…Early applications of the GA approach to the cell formation problem include the work by Venugopal and Narendran (1992) based on minimization of cell load variation and inter-cell moves. Other applications were done by Gravel et al (1998), and Hsu and Su (1998).…”

The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research

“…ACO was inspired by the foraging behavior of real ants (Deneubourg et al (1990)) and its search process can be described as the evolution of a probability distribution over the search process. Venugopal and Narendran (1992) were the first researchers to approach the CF problem using GAs. Their objective was the minimisation of the intercell movements of parts and balancing of loads in the cells.…”